Data Architect

Location: Centurion, Gauteng (provisional – to be confirmed)
Positions Available: 5
Salary: Market-related
Employment Type: To be confirmed

Job Overview

We are seeking experienced and highly skilled Data Architects to design, develop, implement and govern enterprise data architectures within complex organisational and technology environments.

The successful candidates will be responsible for defining enterprise data architecture strategies, developing scalable data models, designing data integration frameworks and ensuring that organisational data platforms support business objectives, operational requirements and long-term technology strategies.

This role requires extensive expertise in enterprise data architecture, data modelling, database design, data integration, data warehousing, cloud data platforms, data governance and information management.

The ideal candidates will have proven experience designing enterprise data solutions, establishing data architecture standards, developing conceptual, logical and physical data models, and supporting complex data modernisation and transformation programmes.

Candidates must demonstrate the ability to translate business information requirements into robust technical data architectures while ensuring data quality, security, scalability, accessibility and regulatory compliance.

The role requires close collaboration with enterprise architects, solution architects, data engineers, database administrators, business analysts, cybersecurity specialists and business stakeholders.

This is a specialist enterprise Data Architect opportunity requiring demonstrable hands-on architecture and data solution design experience. General data analysis, reporting or database administration experience without substantial data architecture responsibilities will not be sufficient.

Key Responsibilities

Enterprise Data Architecture Strategy

• Develop, implement and maintain enterprise data architecture strategies, principles, standards and frameworks.
• Define current-state and target-state data architecture landscapes.
• Align data architecture with organisational objectives and enterprise architecture strategies.
• Develop data architecture blueprints and technology roadmaps.
• Establish standards for enterprise data platforms, databases, data integration and information management.
• Identify architectural gaps, dependencies, risks and improvement opportunities.
• Evaluate emerging data technologies and architectural approaches.
• Support enterprise data modernisation and digital transformation initiatives.
• Define architectural requirements for scalability, availability, performance and resilience.
• Provide technical leadership and guidance on enterprise data architecture decisions.

Enterprise Data Modelling

• Develop conceptual, logical and physical data models.
• Design enterprise data models aligned with business information requirements.
• Define data entities, attributes, relationships, constraints and business rules.
• Apply data modelling standards and naming conventions.
• Develop relational and dimensional data models.
• Design normalised and denormalised database structures where appropriate.
• Maintain enterprise data dictionaries and metadata definitions.
• Review existing data models and recommend improvements.
• Ensure consistency between data models across enterprise systems.
• Support the maintenance of enterprise data model repositories.

Database Architecture and Design

• Design database architectures that support enterprise applications and analytical workloads.
• Evaluate relational, NoSQL and other database technologies against business requirements.
• Define database structures, schemas and data storage approaches.
• Establish database architecture principles and design standards.
• Collaborate with database administrators on performance, availability and recovery requirements.
• Design appropriate data partitioning, indexing and storage strategies.
• Evaluate database scalability and workload requirements.
• Support database consolidation, migration and modernisation initiatives.
• Review database designs for security, integrity and architectural compliance.
• Provide guidance on database technology selection and architectural improvements.

Data Warehousing and Analytical Architecture

• Design enterprise data warehouses, data marts and analytical data platforms.
• Develop dimensional models using star and snowflake schemas.
• Define fact tables, dimension tables and analytical data structures.
• Design data architectures supporting business intelligence and advanced analytics.
• Evaluate modern data warehouse, data lake and lakehouse approaches.
• Support the integration of structured, semi-structured and unstructured data.
• Define data ingestion, transformation and consumption architecture.
• Establish standards for analytical data modelling and information delivery.
• Support reporting, dashboard and analytics requirements.
• Ensure analytical platforms provide reliable, consistent and accessible enterprise information.

Data Integration and Interoperability

• Define enterprise data integration architecture and standards.
• Design batch, real-time and event-driven data integration patterns.
• Develop source-to-target data mappings and integration specifications.
• Establish data exchange standards across enterprise applications.
• Design ETL and ELT architectural approaches.
• Define data pipeline architecture and integration dependencies.
• Support API-based data integration and enterprise interoperability.
• Evaluate messaging, streaming and data replication technologies.
• Collaborate with integration architects and data engineers on solution implementation.
• Ensure data integration solutions meet security, quality and performance requirements.

Cloud Data Architecture

• Design scalable and secure cloud-based data architectures.
• Evaluate cloud-native database, storage and analytical services.
• Develop hybrid and multi-cloud data architecture approaches where required.
• Design cloud data warehouses, data lakes and lakehouse environments.
• Define cloud data ingestion, transformation and processing patterns.
• Establish standards for cloud data security and access management.
• Support cloud data migration and modernisation programmes.
• Evaluate cloud platform performance, availability and cost considerations.
• Collaborate with cloud architects and engineering teams.
• Ensure cloud data solutions align with enterprise architecture and governance requirements.

Data Governance and Information Management

• Develop and maintain enterprise data architecture governance standards.
• Support the implementation of data governance frameworks.
• Define data ownership, stewardship and accountability requirements.
• Establish standards for data classification, metadata and data lineage.
• Support the development of enterprise data dictionaries and business glossaries.
• Define data quality and master data management architecture requirements.
• Promote consistency in enterprise data definitions and structures.
• Support data retention, lifecycle management and information governance.
• Ensure architectural alignment with relevant regulatory and privacy requirements.
• Collaborate with data governance and information security teams.

Master Data and Reference Data Architecture

• Design architecture for master data management (MDM) solutions.
• Define approaches for managing shared enterprise data entities.
• Support the establishment of consistent customer, product, supplier and organisational data definitions.
• Develop reference data architecture and governance standards.
• Identify master data duplication and inconsistency risks.
• Define data synchronisation and distribution patterns.
• Support the design of data quality and matching rules.
• Establish relationships between master data and operational systems.
• Collaborate with business data owners and data stewards.
• Support enterprise information consistency and data integrity.

Data Security, Privacy and Compliance

• Incorporate data security requirements into architecture designs.
• Define architectural controls for data confidentiality, integrity and availability.
• Support data encryption, access control and data protection requirements.
• Collaborate with cybersecurity teams on secure data platform architecture.
• Establish data classification and sensitive information handling requirements.
• Support data masking, anonymisation and tokenisation design where applicable.
• Evaluate data residency, retention and privacy requirements.
• Ensure data architecture supports applicable regulatory obligations, including POPIA where relevant.
• Identify data architecture security risks and recommend mitigations.
• Participate in architecture security and compliance reviews.

Data Migration and Modernisation

• Develop architectural approaches for enterprise data migration initiatives.
• Assess legacy data platforms and identify modernisation opportunities.
• Define source-to-target data architecture requirements.
• Support data mapping, transformation and reconciliation strategies.
• Evaluate migration approaches for large and complex datasets.
• Design target-state data structures and integration dependencies.
• Identify migration risks relating to data quality, compatibility and integrity.
• Collaborate with data migration architects and implementation teams.
• Support data validation and migration readiness assessments.
• Ensure migration solutions align with target enterprise data architecture.

Architecture Governance and Technical Assurance

• Develop and enforce enterprise data architecture principles and standards.
• Review data solution designs for architectural compliance.
• Participate in enterprise architecture review boards.
• Evaluate proposed data technologies and solution designs.
• Maintain architecture decision records and design documentation.
• Identify architectural risks, technical debt and non-compliance.
• Recommend corrective actions and architecture improvements.
• Support architecture assurance throughout project delivery.
• Provide technical guidance to development and data engineering teams.
• Promote consistent, reusable and maintainable enterprise data solutions.

Stakeholder Engagement and Technical Leadership

• Engage with business leaders to understand enterprise information requirements.
• Collaborate with enterprise architects, solution architects and technical specialists.
• Facilitate data architecture and design workshops.
• Present architecture options, recommendations and technical trade-offs.
• Translate complex data architecture concepts into understandable business outcomes.
• Support technology investment and solution selection decisions.
• Provide architectural guidance to data engineers and development teams.
• Resolve cross-system data architecture challenges.
• Support project teams during solution design and implementation.
• Promote data architecture best practices across the organisation.

Minimum Requirements

• Relevant degree in Computer Science, Information Technology, Information Systems, Data Engineering, Software Engineering or a related discipline.
• Typically 7+ years of relevant professional experience in data engineering, database development, enterprise data management or related technical data disciplines.
• Preferably 3+ years of demonstrable hands-on Data Architect or equivalent enterprise data solution architecture experience.
• Proven experience independently designing enterprise data architectures and complex data solutions – essential.
• Strong practical experience developing conceptual, logical and physical data models.
• Advanced knowledge of relational database design and SQL.
• Experience designing enterprise data warehouses, data marts or modern analytical platforms.
• Demonstrated experience with ETL/ELT architecture and enterprise data integration.
• Strong understanding of data modelling methodologies and database design principles.
• Experience with cloud-based data platforms, preferably Microsoft Azure or comparable enterprise cloud technologies.
• Understanding of data lake, lakehouse and modern data platform architectures.
• Experience defining data architecture standards, principles and governance requirements.
• Practical understanding of data security, privacy and information management.
• Experience with data migration, integration or enterprise modernisation initiatives.
• Familiarity with master data management and metadata management principles.
• Experience working with enterprise architecture and solution architecture teams.
• Ability to develop architecture diagrams, technical specifications and design documentation.
• Strong stakeholder engagement, technical leadership and communication skills.
• Proven experience within large or complex enterprise technology environments.

Technical Skills and Competencies

Enterprise Data Architecture

• Enterprise data architecture
• Data architecture strategy
• Current-state and target-state architecture
• Data architecture blueprints
• Enterprise information architecture
• Data architecture roadmaps
• Data platform architecture
• Data architecture governance
• Architecture principles and standards
• Data solution design
• Architecture assurance
• Technical design reviews
• Architecture decision records
• Enterprise architecture alignment

Data Modelling and Database Design

• Conceptual data modelling
• Logical data modelling
• Physical data modelling
• Entity Relationship Diagrams (ERDs)
• Relational database design
• Normalisation and denormalisation
• Dimensional modelling
• Star schemas
• Snowflake schemas
• Data vault modelling
• Data dictionaries
• Data modelling standards
• Schema design
• Data relationships and constraints

Relational Database Technologies

• Microsoft SQL Server
• Azure SQL Database
• Oracle Database
• PostgreSQL
• IBM Db2
• MySQL
• SQL
• T-SQL
• PL/SQL awareness
• Database schemas
• Database performance design
• Data storage architecture
• High availability concepts
• Database scalability
• Data integrity controls

Cloud Data Platforms

Experience with one or more enterprise cloud data ecosystems, such as:

• Microsoft Azure
• Azure Data Lake Storage
• Azure Data Factory
• Azure Synapse Analytics
• Azure SQL
• Azure Databricks
• Microsoft Fabric
• Amazon Web Services (AWS)
• Amazon Redshift
• AWS Glue
• Google BigQuery
• Google Cloud Storage
• Snowflake
• Databricks
• Cloud data lakehouse architectures

Data Integration and Engineering Architecture

• ETL and ELT architecture
• Data pipeline design
• Batch data integration
• Real-time data integration
• Event-driven data architecture
• API-based data integration
• Data replication
• Change Data Capture (CDC)
• Data transformation patterns
• Source-to-target mapping
• Data ingestion architecture
• Enterprise integration patterns
• Data orchestration
• Data integration governance

Modern Data Architecture

• Enterprise data warehouses
• Data lakes
• Data lakehouses
• Data marts
• Data mesh concepts
• Data fabric concepts
• Medallion architecture
• Structured and semi-structured data
• Distributed data processing
• Apache Spark concepts
• Delta Lake
• Streaming data architecture
• Event-driven data processing
• Scalable analytical platforms

Data Modelling and Architecture Tools

Experience with relevant tools such as:

• ER/Studio
• erwin Data Modeler
• SAP PowerDesigner
• Sparx Enterprise Architect
• Microsoft Visio
• Lucidchart
• ArchiMate modelling tools
• LeanIX
• Bizzdesign
• SQL Server Management Studio
• Azure Data Studio
• Other enterprise data modelling and architecture platforms

Data Governance and Information Management

• DAMA-DMBOK principles
• Data governance frameworks
• Data ownership and stewardship
• Data quality architecture
• Data classification
• Data lineage
• Metadata management
• Business glossaries
• Data dictionaries
• Master Data Management (MDM)
• Reference data management
• Data lifecycle management
• Data retention
• Information management standards

Data Security and Compliance

• Data encryption
• Data access controls
• Role-based access control
• Data masking
• Data anonymisation
• Tokenisation concepts
• Data privacy
• POPIA awareness
• Data residency
• Data retention controls
• Secure data integration
• Data security architecture
• Information security governance
• Data platform risk assessment

Data Migration and Modernisation

• Legacy data platform assessment
• Data migration architecture
• Source-to-target data mapping
• Data transformation strategies
• Data reconciliation
• Migration validation
• Database modernisation
• Cloud data migration
• Data platform consolidation
• Migration risk assessment
• Target-state architecture
• Data migration governance

Enterprise Architecture Frameworks

• TOGAF
• DAMA-DMBOK
• Enterprise architecture principles
• ArchiMate fundamentals
• Zachman Framework awareness
• Data architecture reference models
• Architecture governance
• Architecture development methodologies
• Business and IT alignment
• Enterprise transformation architecture

Relevant Certifications (Advantageous)

One or more of the following certifications would be beneficial:

• TOGAF Enterprise Architecture Practitioner
• TOGAF Enterprise Architecture Foundation
• Certified Data Management Professional (CDMP)
• Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
• Microsoft Certified: Fabric Data Engineer Associate (DP-700)
• Microsoft Certified: Azure Data Engineer Associate (DP-203), where previously obtained
• AWS Certified Solutions Architect – Professional
• AWS Certified Data Engineer – Associate
• Google Cloud Professional Data Engineer
• Snowflake SnowPro Core
• Databricks Certified Data Engineer Professional
• Relevant Oracle, SQL Server or IBM Db2 certifications
• Relevant enterprise data modelling or data governance certifications

Key Personal Attributes

• Exceptional technical and analytical problem-solving abilities.
• Strong enterprise architecture and systems thinking.
• Ability to design scalable, secure and maintainable data solutions.
• Excellent conceptual and logical modelling skills.
• Strong attention to detail and architectural consistency.
• Ability to evaluate complex technical requirements and trade-offs.
• Excellent stakeholder engagement and communication skills.
• Strong technical leadership and mentoring abilities.
• Ability to collaborate effectively across architecture, engineering and business teams.
• Strategic thinking with a practical approach to solution delivery.
• Ability to work independently and make sound architectural recommendations.
• Strong documentation and technical presentation skills.
• Commitment to data quality, governance and security.
• Adaptability within evolving technology environments.
• High levels of professionalism, accountability and integrity.

Application Requirements

Interested candidates should submit an updated CV clearly detailing their enterprise data architecture, data modelling, database design and data platform experience, together with copies of relevant academic qualifications and professional certifications.

Candidates should specifically highlight:

• Years of practical Data Architect or enterprise data solution architecture experience.
• Enterprise data architectures personally designed or implemented.
• Conceptual, logical and physical data models developed.
• Enterprise data warehouse, data lake or lakehouse architectures designed.
• Relational database platforms and technologies used.
• Cloud data platforms and services worked with.
• ETL/ELT and enterprise data integration architectures developed.
• Data modelling tools and architecture frameworks applied.
• Data governance, metadata management and MDM experience.
• Data migration and modernisation projects supported or led.
• Data security and privacy architecture responsibilities.
• Architecture governance and technical design review experience.
• The scale and complexity of enterprise environments supported.
• Relevant architecture, cloud, database and data management certifications.

Important: This is a specialist Data Architect opportunity requiring demonstrable experience independently designing enterprise data architectures, data models and complex data solutions. General data analysis, Power BI reporting, SQL development or database administration without substantial architecture and solution design responsibilities will not meet the intended specialist profile.

Please note: This is a provisional recruitment specification prepared pending confirmation of the client's detailed requirements. The preferred data platforms, architecture frameworks, minimum experience, qualifications, certifications, remuneration, employment arrangements and working conditions will be confirmed during the recruitment process.